Research Interests and Achievements

My research work involves a variety of data science, AI-based analytics, clinical and epidemiology research related to blinding age-related ocular diseases, in particular glaucoma, as well as identification of susceptibility genes for ocular traits.

Holistically characterizing the epidemiology of eye diseases

Over the last decade, I have built up one of the largest epidemiological databases - the Singapore Epidemiology of Eye Diseases (SEED) study, for eye diseases in the world. SEED has more than 10,000 participants with detailed phenotypes, genotypes, and bio-banks. Under my leadership, SEED has generated >400 scientific publications, providing novel knowledge and new technology to detect and prevent the most important eye diseases in ageing populations. Importantly, data collected from SEED have been used widely by national and international agencies (e.g., Singapore’s Ministry of Health, World Health Organization, and the Global Burden of Disease program), and clinical guidelines (e.g., 2014 Ministry of Health Diabetes Guidelines, 2016 Asia Pacific Glaucoma Guidelines, and 2017 International Council of Ophthalmology Diabetic Eye Care Guidelines). The SEED data have also been used for healthcare manpower planning (e.g., number of ophthalmologists) and setting up the national diabetic retinopathy screening in Singapore.

Deploying new evidence on eye disease burden to inform global priorities & program

have funded and established the Asian Eye Epidemiology Consortium (AEEC), the largest research networks in the Asia-Pacific region. The overall aim of AEEC is to provide deeper insights on the trends and risk factors of age-related eye diseases among Asians. Under my leadership, the members of AEEC have grown to more than 40 population studies from 10 countries across Asia. The works from AEEC have led to several important publications, such as a landmark paper on the prevalence of geographic atrophy in Asia. Furthermore, my group conducted the largest global analyses on the burden of three major age-related eye diseases: glaucoma, age-related macular degeneration, and diabetic retinopathy. These papers have attracted great attentions from scientific communities and pharmaceutical industry since they were published, and are among the top cited ophthalmology papers. The data were adopted by WHO and other international organizations in guiding public health strategies to manage vision loss for the diverse populations worldwide.

Deciphering the genetic architectures of major eye diseases

I play a key role in several international genetic consortiums on eye diseases, including the leadership on two major consortiums: the Genetics of Asian AMD (GAMA) Consortium, and the International Cataract Genetics Consortium (IGCG). These research works have led to many novel and important genetic discoveries on ocular traits and major eye diseases, including but not limited to age-related macular degeneration in Asians, intraocular pressure, open angle glaucoma, age-related cataract, and myopia-related traits.

Developing AI-based models to address the gaps in screening for blinding eye diseases

To address the gap in screening for eye diseases and detect undiagnosed but referable cases in communities, my group has moved to AI-based analytics for disease prediction and detection. By strong partnership with computer scientists, we have successfully developed novel deep learning algorithms for detecting visual impairment, cataract, and diabetic retinopathy, and algorithms to stratify cardiovascular risks and predict systemic biomarkers based on simple retinal photos.

Defining a novel and important biomarker for angle-closure glaucoma

My prior work provided the first evidence that iris surface textures are important biomarkers for primary angle-closure glaucoma. Through the development of an Asian iris grading scheme, my work comprehensively characterized the iris surface textures for the first time, including the identification of novel associations of iris surface textures with angle-closure anatomic factors. Further investigations showed that crypts on iris surface affect dynamic change of iris volume, and the risk of acute angle closure. The assessment of iris surface textures thus provides a practical approach to assess the risk of angle closure, a highly prevalent conditions in Asians.

Selected Publications

• Tham YC, Goh JH, Anees A, Lei X, Tim TH, Chee MAL. Wang YX Jonas JB, Thakur S, Teo ZL, Cheung N, Hamzah H, Tan GS, Husian R , Sabanayagam C, Wang JJ, Chen Q, Lu Z, Keenan TD, Chey EY, Tan AG, Mitchell P, Goh RS, Xu A, Liu Y, Wong TY, Cheng CY. Detecting visually significant cataract using retinal photograph-based deep learning. Nature Aging. 2022;2:264-271. https://doi.org/10.1038/s43587-022-00171-6
• Rim TH, Lee CJ, Tham YC, Cheung N, Yu M, Lee G, Kim Y, Ting DSW, Chong CCY, Choi YS, Yoo TK, Ryu IH, Baik SJ, Kim YA, Kim SK, Lee SH, Lee BK, Kang SM, Wong EYM, Kim HC, Kim SS*, Park S*, Cheng CY*, Wong TY*. Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs. Lancet Digital Health. 2021 May;3(5):e306-e316. https://doi.org/10.1016/S2589-7500(21)00043-1 *Co-last author
• Tham YC, Anees A, Zhang L, Goh JHL, Rim TH, Nusinovici S, Hamzah H, Chee ML, Tjio G, Li S, Xu X, Goh R, Tang F, Cheung CY, Wang YX, Nangia V, Jonas JB, Gopinath B, Mitchell P, Husain R, Lamoureux E, Sabanayagam C, Wang JJ, Aung T, Liu Y, Wong TY, Cheng CY. Referral for disease-related visual impairment using retinal photograph-based deep learning: a proof-of-concept, model development study. Lancet Digital Health. 2021 Jan;3(1):e29-e40. https://doi.org/10.1016/S2589-7500(20)30271-5
• Gharahkhani P, Jorgenson E, Hysi P, Khawaja AP, Pendergrass S, Han X, Ong JS, Hewitt AW, Segrè AV, Rouhana JM, Hamel AR, Igo RP Jr, Choquet H, Qassim A, Josyula NS, Cooke Bailey JN, Bonnemaijer PWM, Iglesias A, Siggs OM, Young TL, Vitart V, Thiadens AAHJ, Karjalainen J, Uebe S, Melles RB, Nair KS, Luben R, Simcoe M, Amersinghe N, Cree AJ, Hohn R, Poplawski A, Chen LJ, Rong SS, Aung T, Vithana EN; NEIGHBORHOOD consortium; ANZRAG consortium; Biobank Japan project; FinnGen study; UK Biobank Eye and Vision Consortium; GIGA study group; 23 and Me Research Team, Tamiya G, Shiga Y, Yamamoto M, Nakazawa T, Currant H, Birney E, Wang X, Auton A, Lupton MK, Martin NG, Ashaye A, Olawoye O, Williams SE, Akafo S, Ramsay M, Hashimoto K, Kamatani Y, Akiyama M, Momozawa Y, Foster PJ, Khaw PT, Morgan JE, Strouthidis NG, Kraft P, Kang JH, Pang CP, Pasutto F, Mitchell P, Lotery AJ, Palotie A, van Duijn C, Haines JL, Hammond C, Pasquale LR, Klaver CCW, Hauser M, Khor CC, Mackey DA, Kubo M, Cheng CY, Craig JE, MacGregor S, Wiggs JL. Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries. Nat Commun. 2021 Feb 24;12(1):1258. https://doi.org/10.1038/s41467-020-20851-4 *Co-last author
• Gharahkhani P, Jorgenson E, Hysi P, Khawaja AP, Pendergrass S, Han X, Ong JS, Hewitt AW, Segrè AV, Rouhana JM, Hamel AR, Igo RP Jr, Choquet H, Qassim A, Josyula NS, Cooke Bailey JN, Bonnemaijer PWM, Iglesias A, Siggs OM, Young TL, Vitart V, Thiadens AAHJ, Karjalainen J, Uebe S, Melles RB, Nair KS, Luben R, Simcoe M, Amersinghe N, Cree AJ, Hohn R, Poplawski A, Chen LJ, Rong SS, Aung T, Vithana EN; NEIGHBORHOOD consortium; ANZRAG consortium; Biobank Japan project; FinnGen study; UK Biobank Eye and Vision Consortium; GIGA study group; 23 and M Research Team, Tamiya G, Shiga Y, Yamamoto M, Nakazawa T, Currant H, Birney E, Wang X, Auton A, Lupton MK, Martin NG, Ashaye A, Olawoye O, Williams SE, Akafo S, Ramsay M, Hashimoto K, Kamatani Y, Akiyama M, Momozawa Y, Foster PJ, Khaw PT, Morgan JE, Strouthidis NG, Kraft P, Kang JH, Pang CP, Pasutto F, Mitchell P, Lotery AJ, Palotie A, van Duijn C, Haines JL, Hammond C, Pasquale LR, Klaver CCW, Hauser M, Khor CC, Mackey DA, Kubo M, Cheng CY*, Craig JE*, MacGregor S*, Wiggs JL*. Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries. Nat Commun. 2021;12(1):1258. https://doi.org/10.1038/s41467-020-20851-4 *Co-last author
• Rim TH, Lee G, Kim Y, Tham YC, Lee CJ, Baik SJ, Kim YA, Yu M, Deshmukh M, Lee BK, Park S, Kim HC, Sabayanagam C, Ting DSW, Wang YX, Jonas JB, Kim SS, Wong TY, Cheng CY. Prediction of systemic biomarkers from retinal photographs development and validation of deep-learning algorithms. Lancet Digital Health. 2020 Oct;2(10):e526-e536. https://doi.org/10.1016/S2589-7500(20)30216-8
• Ting DSW, Cheung CY, Lim G, Tan GSW, Quang ND, Gan A, Hamzah H, Garcia-Franco R, San Yeo IY, Lee SY, Wong EYM, Sabanayagam C, Baskaran M, Ibrahim F, Tan NC, Finkelstein EA, Lamoureux EL, Wong IY, Bressler NM, Sivaprasad S, Varma R, Jonas JB, He MG, Cheng CY*, Cheung GCM*, Aung T*, Hsu W*, Lee ML*, Wong TY*. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multi-ethnic populations with diabetes. JAMA. 2017 Dec 12;318(22):2211-2223. https://doi.org/10.1001/jama.2017.18152 *Co-last author
• Cheng CY, Yamashiro K, Chen LJ, Ahn J, Huang L, Huang L, Cheung CM, Miyake M, Cackett PD, Yeo IY, Laude A, Mathur R, Pang J, Sim KS, Koh AH, Chen P, Lee SY, Wong D, Chan CM, Loh BK, Sun Y, Davila S, Nakata I, Nakanishi H, Akagi-Kurashige Y, Gotoh N, Tsujikawa A, Matsuda F, Mori K, Yoneya S, Sakurada Y, Iijima H, Iida T, Honda S, Lai TY, Tam PO, Chen H, Tang S, Ding X, Wen F, Lu F, Zhang X, Shi Y, Zhao P, Zhao B, Sang J, Gong B, Dorajoo R, Yuan JM, Koh WP, van Dam RM, Friedlander Y, Lin Y, Hibberd ML, Foo JN, Wang N, Wong CH, Tan GS, Park SJ, Bhargava M, Gopal L, Naing T, Liao J, Ong PG, Mitchell P, Zhou P, Xie X, Liang J, Mei J, Jin X, Saw SM, Ozaki M, Mizoguchi T, Kurimoto Y, Woo SJ, Chung H, Yu HG, Shin JY, Park DH, Kim IT, Chang W, Sagong M, Lee SJ, Kim HW, Lee JE, Li Y, Liu J, Teo YY, Heng CK, Lim TH, Yang SK, Song K, Vithana EN, Aung T, Bei JX, Zeng YX, Tai ES, Li XX, Yang Z, Park KH, Pang CP, Yoshimura N, Wong TY, Khor CC. New loci and coding variants confer risk for age-related macular degeneration in East Asians. Nat Commun. 2015 Jan 28;6:6063. https://doi.org/10.1038/ncomms7063
• Hysi PG*, Cheng CY*, Springelkamp H*, Macgregor S*, Bailey JN*, Wojciechowski R*, Vitart V, Nag A, Hewitt AW, Höhn R, Venturini C, Mirshahi A, Ramdas WD, Thorleifsson G, Vithana E, Khor CC, Stefansson AB, Liao J, Haines JL, Amin N, Wang YX, Wild PS, Ozel AB, Li JZ, Fleck BW, Zeller T, Staffieri SE, Teo YY, Cuellar-Partida G, Luo X, Allingham RR, Richards JE, Senft A, Karssen LC, Zheng Y, Bellenguez C, Xu L, Iglesias AI, Wilson JF, Kang JH, van Leeuwen EM, Jonsson V, Thorsteinsdottir U, Despriet DD, Ennis S, Moroi SE, Martin NG, Jansonius NM, Yazar S, Tai ES, Amouyel P, Kirwan J, van Koolwijk LM, Hauser MA, Jonasson F, Leo P, Loomis SJ, Fogarty R, Rivadeneira F, Kearns L, Lackner KJ, de Jong PT, Simpson CL, Pennell CE, Oostra BA, Uitterlinden AG, Saw SM, Lotery AJ, Bailey-Wilson JE, Hofman A, Vingerling JR, Maubaret C, Pfeiffer N, Wolfs RC, Lemij HG, Young TL, Pasquale LR, Delcourt C, Spector TD, Klaver CC, Small KS, Burdon KP, Stefansson K, Wong TY; BMES GWAS Group; NEIGHBORHOOD Consortium; Wellcome Trust Case Control Consortium 2, Viswanathan A, Mackey DA, Craig JE, Wiggs JL, van Duijn CM, Hammond CJ, Aung T. Genome-wide analysis of multi-ancestry cohorts identifies new loci influencing intraocular pressure and susceptibility to glaucoma. Nat Genet. 2014 Oct;46(10):1126-1130. https://doi.org/10.1038/ng.3087 *Co-first author
• Tham YC, Li X, Wong TY, Quigley HA, Aung T, Cheng CY. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology. 2014 Nov;121(11):2081-90. https://doi.org/10.1016/j.ophtha.2014.05.013
• Wong WL, Su X, Li X, Cheung CMG, Klein R, Cheng CY*, Wong TY*. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: A systematic review and meta-analysis. Lancet Glob Health. 2014 Feb;2(2):e106-16. https://doi.org/10.1016/S2214-109X(13)70145-1 *Co-last author

Collaborations

View more details on the collaborations here